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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260417T190156Z
LOCATION:West Building\, Rooms 220-222
DTSTART;TZID=America/Los_Angeles:20250814T091000
DTEND;TZID=America/Los_Angeles:20250814T092000
UID:siggraph_SIGGRAPH 2025_sess134_papers_1013@linklings.com
SUMMARY:Stochastic Barnes-Hut Approximation for Fast Summation on the GPU
DESCRIPTION:Abhishek Madan (University of Toronto); Nicholas Sharp, Franci
 s Williams, and Ken Museth (NVIDIA); and David I.W. Levin (University of T
 oronto, NVIDIA)\n\nWe present a novel stochastic version of the Barnes-Hut
  approximation. Regarding the level-of-detail (LOD) family of approximatio
 ns as control variates, we construct an unbiased estimator of the kernel s
 um being approximated. Through several examples in graphics, we demonstrat
 e that our method outperforms a GPU-optimized implementation of the determ
 inistic Barnes-Hut approximation.\n\nInterest Area: Research & Education\n
 \nRecording: Livestreamed, Not Livestreamed, Recorded, Not Recorded\n\nReg
 istration Category: Full Conference, Virtual Access, Thursday\n\nSession C
 hair: Edward Chien (Boston University)\n\n
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